Covalent inhibition has become more accepted in the past two decades, as illustrated by the clinical approval of several irreversible inhibitors designed to covalently modify their target. Elucidation of the structure‐activity relationship and potency of such inhibitors requires a detailed kinetic evaluation. Here, we elucidate the relationship between the experimental read‐out and the underlying inhibitor binding kinetics. Interactive kinetic simulation scripts are employed to highlight the effects of in vitro enzyme activity assay conditions and inhibitor binding mode, thereby showcasing which assumptions and corrections are crucial. Four stepwise protocols to assess the biochemical potency of (ir)reversible covalent enzyme inhibitors targeting a nucleophilic active site residue are included, with accompanying data analysis tailored to the covalent binding mode. Together, this will serve as a guide to make an educated decision regarding the most suitable method to assess covalent inhibition potency. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.Basic Protocol I: Progress curve analysis of substrate association competitionBasic Data Analysis Protocol 1A: Two‐step irreversible covalent inhibitionBasic Data Analysis Protocol 1B: One‐step irreversible covalent inhibitionBasic Data Analysis Protocol 1C: Two‐step reversible covalent inhibitionBasic Data Analysis Protocol 1D: Two‐step irreversible covalent inhibition with substrate depletionBasic Protocol II: Incubation time–dependent potency IC₅₀(t)Basic Data Analysis Protocol 2: Two‐step irreversible covalent inhibitionBasic Protocol III: Preincubation time–dependent inhibition without dilutionBasic Data Analysis Protocol 3: Preincubation time–dependent inhibition without dilutionBasic Data Analysis Protocol 3Ai: Two‐step irreversible covalent inhibitionAlternative Data Analysis Protocol 3Aii: Two‐step irreversible covalent inhibitionBasic Data Analysis Protocol 3Bi: One‐step irreversible covalent inhibitionAlternative Data Analysis Protocol 3Bii: One‐step irreversible covalent inhibitionBasic Data Analysis Protocol 3C: Two‐step reversible covalent inhibitionBasic Protocol IV: Preincubation time–dependent inhibition with dilution/competitionBasic Data Analysis Protocol 4: Preincubation time–dependent inhibition with dilutionBasic Data Analysis Protocol 4Ai: Two‐step irreversible covalent inhibitionAlternative Data Analysis Protocol 4Aii: Two‐step irreversible covalent inhibitionBasic Data Analysis Protocol 4Bi: One‐step irreversible covalent inhibitionAlternative Data Analysis Protocol 4Bii: One‐step irreversible covalent inhibition

Cryo-electron tomography provides 3D images of macromolecules in their cellular context. To detect macromolecules in tomograms, template matching (TM) is often used, which uses 3D models that are often reliable for substantial parts of the macromolecules. However, the extent of rotational searches in particle detection has not been investigated due to computational limitations. Here, we provide a GPU implementation of TM as part of the PyTOM software package, which drastically speeds up the orientational search and allows for sampling beyond the Crowther criterion within a feasible timeframe. We quantify the improvements in sensitivity and false-discovery rate for the examples of ribosome identification and detection. Sampling at the Crowther criterion, which was effectively impossible with CPU implementations due to the extensive computation times, allows for automated extraction with high sensitivity. Consequently, we also show that an extensive angular sample renders 3D TM sensitive to the local alignment of tilt series and damage induced by focused ion beam milling. With this new release of PyTOM, we focused on integration with other software packages that support more refined subtomogram-averaging workflows. The automated classification of ribosomes by TM with appropriate angular sampling on locally corrected tomograms has a sufficiently low false-discovery rate, allowing for it to be directly used for high-resolution averaging and adequate sensitivity to reveal polysome organization.

The algorithmic development in the field of path sampling has made tremendous progress in recent years. Although the original transition path sampling method was mostly used as a qualitative tool to sample reaction paths, the more recent family of interface‐based path sampling methods has paved the way for more quantitative rate calculation studies. Of the exact methods, the replica exchange transition interface sampling (RETIS) method is the most efficient, but rather difficult to implement. This has been the main motivation to develop the open‐source Python‐based computer library PyRETIS that was released in 2017. PyRETIS is designed to be easily interfaced with any molecular dynamics (MD) package using either classical or ab initio MD. In this study, we report on the principles and the software enhancements that are now included in PyRETIS 2, as well as the recent developments on the user interface, improvements of the efficiency via the implementation of new shooting moves, easier initialization procedures, analysis methods, and supported interfaced software. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.

• pytom-match-pick is a GPU-accelerated software for template matching in cryo-electron tomograms. • A novel application of a tophat transform on score maps is tested and proven effective at filtering peaks. • The tophat transform is integrated into a dual-constraint thresholding strategy which improves classification of macromolecules in a simulated dataset. • In experimental data, the dual-constraint thresholding strategy leads to improved subtomogram averages.

Permeation of compounds through membranes is important in biological and engineering processes, e.g., drug delivery through lipid bilayers, anesthetics, or chemical reactor design. Simulations at the atomic scale can provide insight in the diffusive pathways and they give estimates of the membrane permeability based on counting membrane transitions or on the inhomogeneous solubility-diffusivity model described by the Smoluchowski equation. For many permeants, permeation through a membrane is too slow to gather sufficient statistics with conventional molecular dynamics simulations, i.e., permeation is a rare event. Recent attempts to improve the description of the dynamics of such rare permeation events have been based on milestoning, which allows the study of processes at timescales beyond those achievable by straightforward molecular dynamics. The approach is not relying on an overdamped description, but, still, it uses a Markovian approximation which is only valid for small permeants that are not disruptive to the membrane structure. To overcome this fundamental limitation, we show here how replica exchange transition interface sampling (RETIS) can effectively be used on this problem by deriving an effective set of equations that relate the outcome of RETIS simulations and the permeability coefficient. In addition, we introduce two new path Monte Carlo (MC) moves specifically for permeation dynamics, that are used in combination with the ordinary path generating moves, which considerably increase the efficiency. The advantage of our method is that it gives exact results, identical to brute force molecular dynamics, but orders of magnitude faster.

Capturing rare yet pivotal events poses a significant challenge for molecular simulations. Path sampling provides a unique approach to tackle this issue without altering the potential energy landscape or dynamics, enabling recovery of both thermodynamic and kinetic information. However, despite its exponential acceleration compared to standard molecular dynamics, generating numerous trajectories can still require a long time. By harnessing our recent algorithmic innovations—particularly subtrajectory moves with high acceptance, coupled with asynchronous replica exchange featuring infinite swaps—we establish a highly parallelizable and rapidly converging path sampling protocol, compatible with diverse high-performance computing architectures. We demonstrate our approach on the liquid–vapor phase transition in superheated water, the unfolding of the chignolin protein, and water dissociation. The latter, performed at the ab initio level, achieves comparable statistical accuracy within days, in contrast to a previous study requiring over a year.